The Argument Over a Long-Standing Autism Intervention

Jessica Winter

The New Yorker

Originally posted 12 Feb 24

Here are excerpts:

A.B.A. is the only autism intervention that is approved by insurers and Medicaid in all fifty states. The practice is widely recommended for autistic kids who exhibit dangerous behaviors, such as self-injury or aggression toward others, or who need to acquire basic skills, such as dressing themselves or going to the bathroom. The mother of a boy with severe autism in New York City told me that her son’s current goals in A.B.A. include tolerating the shower for incrementally longer intervals, redirecting the urge to pull on other people’s hair, and using a speech tablet to say no. Another kid might be working on more complex language skills by drilling with flash cards or honing his ability to focus on academic work. Often, A.B.A. targets autistic traits that may be socially stigmatizing but are harmless unto themselves, such as fidgeting, avoiding eye contact, or stereotypic behaviors commonly known as stimming—rocking, hand-flapping, and so forth.

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In recent years, A.B.A. has come under increasingly vehement criticism from members of the neurodiversity movement, who believe that it cruelly pathologizes autistic behavior. They say that its rewards for compliance are dehumanizing; some compare A.B.A. to conversion therapy. Social-media posts condemning the practice often carry the hashtag #ABAIsAbuse. The message that A.B.A. sends is that “your instinctual way of being is incorrect,” Zoe Gross, the director of advocacy at the nonprofit Autistic Self Advocacy Network, told me. “The goals of A.B.A. therapy—from its inception, but still through today—tend to focus on teaching autistic people to behave like non-autistic people.” But others say this criticism obscures the good work that A.B.A. can do. Alicia Allgood, a board-certified behavior analyst who co-runs an A.B.A. agency in New York City, and who is herself autistic, told me, “The autistic community is up in arms. There is a very vocal part of the autistic population that is saying that A.B.A. is harmful or aversive or has potentially caused trauma.”

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In recent years, private equity has taken a voracious interest in A.B.A. services, partly because they are perceived as inexpensive. Private-equity firms have consolidated many small clinics into larger chains, where providers are often saddled with unrealistic billing quotas and cut-and-paste treatment plans. Last year, the Center for Economic and Policy Research published a startling report on the subject, which included an account of how Blackstone effectively bankrupted a successful A.B.A. provider and shut down more than a hundred of its treatment sites. Private-equity-owned A.B.A. chains have been accused of fraudulent billing and wage theft; message boards for A.B.A. providers overflow with horror stories about low pay, churn, and burnout. High rates of turnover are acutely damaging to a specialty that relies on familiarity between provider and client. “The idea that we could just franchise A.B.A. providers and anyone could do the work—that was misinformed,” Singer, of the Autism Science Foundation, said.

The info is here.

Tackling healthcare AI's bias, regulatory and inventorship challenges

Bill Siwicki

Healthcare IT News

Originally posted 29 August 23

While AI adoption is increasing in healthcare, there are privacy and content risks that come with technology advancements.

Healthcare organizations, according to Dr. Terri Shieh-Newton, an immunologist and a member at global law firm Mintz, must have an approach to AI that best positions themselves for growth, including managing:

• Biases introduced by AI. Provider organizations must be mindful of how machine learning is integrating racial diversity, gender and genetics into practice to support the best outcome for patients.

• Inventorship claims on intellectual property. Identifying ownership of IP as AI begins to develop solutions in a faster, smarter way compared to humans.

Healthcare IT News sat down with Shieh-Newton to discuss these issues, as well as the regulatory landscape’s response to data and how that impacts AI.

Q. Please describe the generative AI challenge with biases introduced from AI itself. How is machine learning integrating racial diversity, gender and genetics into practice?

A. Generative AI is a type of machine learning that can create new content based on the training of existing data. But what happens when that training set comes from data that has inherent bias? Biases can appear in many forms within AI, starting from the training set of data.

Take, as an example, a training set of patient samples already biased if the samples are collected from a non-diverse population. If this training set is used for discovering a new drug, then the outcome of the generative AI model can be a drug that works only in a subset of a population – or have just a partial functionality.

Some traits of novel drugs are better binding to its target and lower toxicity. If the training set excludes a population of patients of a certain gender or race (and the genetic differences that are inherent therein), then the outcome of proposed drug compounds is not as robust as when the training sets include a diversity of data.

This leads into questions of ethics and policies, where the most marginalized population of patients who need the most help could be the group that is excluded from the solution because they were not included in the underlying data used by the generative AI model to discover that new drug.

One can address this issue with more deliberate curation of the training databases. For example, is the patient population inclusive of many types of racial backgrounds? Gender? Age ranges?

By making sure there is a reasonable representation of gender, race and genetics included in the initial training set, generative AI models can accelerate drug discovery, for example, in a way that benefits most of the population.

The info is here. 

Here is my take:

 One of the biggest challenges is bias. AI systems are trained on data, and if that data is biased, the AI system will be biased as well. This can have serious consequences in healthcare, where biased AI systems could lead to patients receiving different levels of care or being denied care altogether.

Another challenge is regulation. Healthcare is a highly regulated industry, and AI systems need to comply with a variety of laws and regulations. This can be complex and time-consuming, and it can be difficult for healthcare organizations to keep up with the latest changes.

Finally, the article discusses the challenges of inventorship. As AI systems become more sophisticated, it can be difficult to determine who is the inventor of a new AI-powered healthcare solution. This can lead to disputes and delays in bringing new products and services to market.

The article concludes by offering some suggestions for how to address these challenges:

• To reduce bias, healthcare organizations need to be mindful of the data they are using to train their AI systems. They should also audit their AI systems regularly to identify and address any bias.
• To comply with regulations, healthcare organizations need to work with experts to ensure that their AI systems meet all applicable requirements.
• To resolve inventorship disputes, healthcare organizations should develop clear policies and procedures for allocating intellectual property rights.

By addressing these challenges, healthcare organizations can ensure that AI is deployed in a way that is safe, effective, and ethical.

Additional thoughts

In addition to the challenges discussed in the article, there are a number of other factors that need to be considered when deploying AI in healthcare. For example, it is important to ensure that AI systems are transparent and accountable. This means that healthcare organizations should be able to explain how their AI systems work and why they make the decisions they do.

It is also important to ensure that AI systems are fair and equitable. This means that they should treat all patients equally, regardless of their race, ethnicity, gender, income, or other factors.

Finally, it is important to ensure that AI systems are used in a way that respects patient privacy and confidentiality. This means that healthcare organizations should have clear policies in place for the collection, use, and storage of patient data.

By carefully considering all of these factors, healthcare organizations can ensure that AI is used to improve patient care and outcomes in a responsible and ethical way.

Disrupting the System Constructively: Testing the Effectiveness of Nonnormative Nonviolent Collective Action

Shuman, E. (2020, June 21). 

PsyArXiv

https://doi.org/10.31234/osf.io/rvgup

Abstract

Collective action research tends to focus on motivations of the disadvantaged group, rather than on which tactics are effective at driving the advantaged group to make concessions to the disadvantaged. We focused on the potential of nonnormative nonviolent action as a tactic to generate support for concessions among advantaged group members who are resistant to social change. We propose that this tactic, relative to normative nonviolent and to violent action, is particularly effective because it reflects constructive disruption: a delicate balance between disruption (which can put pressure on the advantaged group to respond), and perceived constructive intentions (which can help ensure that the response to action is a conciliatory one). We test these hypotheses across four contexts (total N = 3650). Studies 1-3 demonstrate that nonnormative nonviolent action (compared to inaction, normative nonviolent action, and violent action) is uniquely effective at increasing support for concessions to the disadvantaged among resistant advantaged group members (compared to advantaged group members more open to social change). Study 3 shows that constructive disruption mediates this effect. Study 4 shows that perceiving a real-world ongoing protest as constructively disruptive predicts support for the disadvantaged, while Study 5 examines these processes longitudinally over 2 months in the context of an ongoing social movement. Taken together, we show that nonnormative nonviolent action can be an effective tactic for generating support for concessions to the disadvantaged among those who are most resistant because it generates constructive disruption.

From the General Discussion

Practical Implications

Based on this research, which collective action tactic should disadvantaged groups choose to advance their status? While a simple reading of these findings might suggest that nonnormative nonviolent action is the “most effective” form of action, a closer reading of these findings and other research (Saguy & Szekeres, 2018; Teixeira et al., 2020; Thomas & Louis, 2014) would suggest that what type of action is most effective depends on the goal. We demonstrate that nonnormative nonviolent action is effective for generating support for concessions to the protest that would advance its policy goals from those who were more resistant. On the other hand, other prior research has found that normative nonviolent action was more effective at turning sympathizers into active supporters (Teixeira et al., 2020; Thomas & Louis, 2014)16. Thus, which action tactic will be most useful to the disadvantaged may depend on the goal: If they are facing resistance from the advantaged blocking the achievement of their goals, nonnormative nonviolent action may be more effective. However, if the disadvantaged are seeking to build a movement that includes members of the advantaged group, then normative nonviolent action will likely be more effective. The question is thus not which tactic is “most effective”, but which tactic is most effective to achieve which goal for what audience.

The research is here.

How FDA Failures Contributed to the Opioid Crisis

Andrew Kolodny, MD

AMA J Ethics. 2020;22(8):E743-750. 

doi: 10.1001/amajethics.2020.743.

Abstract

Over the past 25 years, pharmaceutical companies deceptively promoted opioid use in ways that were often neither safe nor effective, contributing to unprecedented increases in prescribing, opioid use disorder, and deaths by overdose. This article explores regulatory mistakes made by the US Food and Drug Administration (FDA) in approving and labeling new analgesics. By understanding and correcting these mistakes, future public health crises caused by improper pharmaceutical marketing might be prevented.

Introduction

In the United States, opioid use disorder (OUD) and opioid overdose were once rare. But over the past 25 years, the number of Americans suffering from OUD increased exponentially and in parallel with an unprecedented increase in opioid prescribing. Today, OUD is common, especially in patients with chronic pain treated with opioid analgesics, and opioid overdose is the leading cause of accidental death.

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Oversight Recommendations

While fewer clinicians are initiating long-term opioids, overprescribing is still a problem. According to a recently published report, more than 2.9 million people initiated opioid use in December 2017. The FDA’s continued approval of new opioids exacerbates this problem. Each time a branded opioid hits the market, the company, eager for return on its investment, is given an incentive and, in essence, a license to promote aggressive prescribing. The FDA’s continued approval of new opioids pits the financial interests of drug companies against city, state, and federal efforts to discourage initiation of long-term opioids.

To finally end the opioid crisis, the FDA must enforce the Food, Drug, and Cosmetic Act, and it must act on recommendations from the NAS for an overhaul of its opioid approval and removal policies. The broad indication on opioid labels must be narrowed, and an explicit warning against long-term use and high-dose prescribing should be added. The label should reinforce, rather than contradict, guidance from the CDC, the Department of Veterans Affairs, the Agency for Healthcare Research and Quality, and other public health agencies that are calling for more cautious prescribing.

The information is here.

How Does Cost-Effectiveness Analysis Inform Health Care Decisions?

David D. Kim & Anirban Basu

AMA J Ethics. 2021;23(8):E639-647. 

doi: 10.1001/amajethics.2021.639.

Abstract

Cost-effectiveness analysis (CEA) provides a formal assessment of trade-offs involving benefits, harms, and costs inherent in alternative options. CEA has been increasingly used to inform public and private organizations’ reimbursement decisions, benefit designs, and price negotiations worldwide. Despite the lack of centralized efforts to promote CEA in the United States, the demand for CEA is growing. This article briefly reviews the history of CEA in the United States, highlights advances in practice guidelines, and discusses CEA’s ethical challenges. It also offers a way forward to inform health care decisions.

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Ethical Considerations

There have been a few criticisms on ethical grounds of CEA’s use for decision making. These include (1) controversies associated with the use of QALYs, (2) distributive justice, and (3) incomplete valuation. We discuss each of them in detail here. However, it is worth pointing out that cost-effectiveness evidence is only one of many factors considered in resource allocation decisions. We have found that none of the international HTA bodies bases its decisions solely on cost-effectiveness evidence. Therefore, much of CEA’s criticisms, fair or not, can be addressed through deliberative processes.

QALYs. The lower health utility, or health-related quality of life, assigned to patients with worse health (because of more severe disease, disability, age, and so on) raises distributional issues in using QALYs for resource allocation decisions. For example, because patients with disabilities have a lower overall health utility weight, any extension of their lives by reducing the health burden from one disease “would not generate as many QALYs as a similar extension of life for otherwise healthy people.” This distributional limitation arises because of the multiplicative nature of QALYs, which are a product of life-years and health utility weight. Consequently, the National Council on Disability has strongly denounced the use of QALYs.

Alternatives to QALYs have been proposed. The Institute for Clinical and Economic Review has started using the equal value of life-years gained metric, a modified version of the equal value of life (EVL) metric, to supplement QALYs. In EVL calculations, any life-year gained is valued at a weight of 1 QALY, irrespective of individuals’ health status during the extra year. EVL, however, “has had limited traction among academics and decision-making bodies” because it undervalues interventions that extend life-years by the same amount as other interventions but that substantially improve quality of life. More recently, a health-years-in-total metric was proposed to overcome the limitations of both QALYs and EVL, but more work is needed to fully understand its theoretical foundations.

The info is here.

Do antidepressants work?

Jacob Stegenga

aeon.co

Originally published 5 Mar 19

Here is an excerpt:

To see this, consider an analogy. Imagine we are testing a drug for weight loss. For every 100 subjects in the drug group, three subjects lose one kilogramme and 97 subjects gain five kilos. For every 100 subjects in the placebo group, two lose four kilos and 98 subjects do not gain or lose any weight. How effective is the drug for weight loss? The odds ratio of weight loss is 1.5, and yet this number tells us nothing about how much weight people on average gain or lose – indeed, the number entirely conceals the real effects of the drug. Though this is an extreme analogy, it shows how cautious we must be when interpreting this celebrated meta-analysis. Unfortunately, however, in response to this work, many leading psychiatrists celebrated, and news headlines misleadingly claimed ‘The drugs do work.’ On the winding route from the hard work of these researchers to the news reports where you were most likely to hear about that study, a simple number became a lie.

When analysed properly, the best evidence indicates that antidepressants are not clinically beneficial. The meta-analyses worth considering, such as the one above, involve attempts to gather evidence from all trials on antidepressants, including those that remain unpublished. Of course it is impossible to know that a meta-analysis includes all unpublished evidence, because publication bias is characterised by deception, either inadvertent or wilful. Nevertheless, these meta-analyses are serious attempts to address publication bias by finding as much data as possible. What, then, do they show?

In meta-analyses that include as much of the evidence as possible, the severity of depression among subjects who receive antidepressants goes down by approximately two points compared with subjects who receive a placebo. Two points. Remember, a depression score can go down by double that amount simply if a subject stops fidgeting. This result, found by both champions and critics of antidepressants, has been replicated year after year for more than a decade (see, for example, the meta-analyses led by Irving Kirsch in 2008, by J C Fournier in 2010, and by Janus Christian Jakobsen in 2017). The phenomena of blind-breaking, the placebo effect and unresolved publication bias could easily account for this trivial two-point reduction in severity scores.

The info is here.

Disrupting the System Constructively: Testing the Effectiveness of Nonnormative Nonviolent Collective Action

Shuman, E. (2020, June 21).
https://doi.org/10.31234/osf.io/rvgup

Abstract

Collective action research tends to focus on motivations of the disadvantaged group, rather than on which tactics are effective at driving the advantaged group to make concessions to the disadvantaged. We focused on the potential of nonnormative nonviolent action as a tactic to generate support for concessions among advantaged group members who are resistant to social change. We propose that this tactic, relative to normative nonviolent and to violent action, is particularly effective because it reflects constructive disruption: a delicate balance between disruption (which can put pressure on the advantaged group to respond), and perceived constructive intentions (which can help ensure that the response to action is a conciliatory one). We test these hypotheses across four contexts (total N = 3650). Studies 1-3 demonstrate that nonnormative nonviolent action (compared to inaction, normative nonviolent action, and violent action) is uniquely effective at increasing support for concessions to the disadvantaged among resistant advantaged group members (compared to advantaged group members more open to social change). Study 3 shows that constructive disruption mediates this effect. Study 4 shows that perceiving a real-world ongoing protest as constructively disruptive predicts support for the disadvantaged, while Study 5 examines these processes longitudinally over 2 months in the context of an ongoing social movement. Taken together, we show that nonnormative nonviolent action can be an effective tactic for generating support for concessions to the disadvantaged among those who are most resistant because it generates constructive disruption.

From the General Discussion

Based on this research, which collective action tactic should disadvantaged groups choose to advance their status? While a simple reading of these findings might suggest that nonnormative nonviolent action is the “most effective” form of action, a closer reading of these findings and other research (Saguy & Szekeres, 2018; Teixeira et al., 2020; Thomas & Louis, 2014) would suggest that what type of action is most effective depends on the goal. We demonstrate that nonnormative nonviolent action is effective for generating support for concessions to the protest that would advance its policy goals from those who were more resistant. On the other hand, other prior research has found that normative nonviolent action was more effective at turning sympathizers into active supporters (Teixeira et al., 2020; Thomas & Louis, 2014)16. Thus, which action tactic will be most useful to the disadvantaged may depend on the goal: If they are facing resistance from the advantaged blocking the achievement of their goals, nonnormative nonviolent action may be more effective. However, if the disadvantaged are seeking to build a movement that includes members of the advantaged group, the nonnormative nonviolent action will likely be more effective. The question is thus not which tactic is “most effective”, but which tactic is most effective to achieve which goal for what audience.

Hydroxychloroquine RCTs: 'Ethically, the Choice Is Clear'

F. Perry Wilson
medscape.com
Originally poste 5 August 20

Here is an excerpt:

I am not going to say that HCQ has no effect on COVID-19. We can never be 100% sure of that. But I am sure that if it has an effect, it is quite small. Think of a world where HCQ was a miracle cure for COVID-19. Think how different all of these randomized trials would look. It would be immediately obvious.

Straight talk: HCQ is unlikely to kill you. It will kill someone (rare cases of torsades de pointes occur), but it is unlikely to be you or your patients. It really is a relatively well-tolerated drug. But there are adverse effects, as all of these trials show. And given that, our ethical obligation to "first, do no harm" is paramount here. There simply is not good evidence that HCQ has a robust effect, and there is evidence of at least moderate harm. Ethically, the choice is clear.

A few final caveats. Yes, only one of these trials reported on the use of zinc with HCQ (no effect, by the way). But two things on that particular issue: First, we know that many individuals take zinc supplements, so if, as the argument goes, HCQ is a miracle cure when given with zinc, you'd still see a benefit in an HCQ trial because a subset of people — maybe 25% — are taking zinc.

The zinc issue falls into this "no true Scotsman" land of HCQ studies. Any negative study can be dismissed: "Oh, you didn't give it early enough, or late enough, or with zinc, or with azithromycin, or on Sunday," or whatever. That's not how science works. I'm not saying that any of these studies are perfect, just that they are the best evidence we have right now. The burden of proof is to show that the drug works. Though I'm sure that pharma would be stoked to be able to argue that their latest negative trial can be ignored because their billion-dollar drug wasn't given in concert with vitamin C or whatever.

Yes, I know that another Yale professor is saying that HCQ can save lives.

And to those of you who have pointed out that he is a full professor while I am a mere associate professor, you really know how to hurt a guy. I have no idea why he wrote that article and didn't mention any of the randomized trials. But I embrace the academic freedom that he and I both have to present our best interpretation of the data.

The info is here.

Business gets ready to trip

Jeffrey O'Brien
Forbes. com
Originally posted 17 Feb 20

Here is an excerpt:

The need for a change in approach is clear. “Mental illness” is an absurdly large grab bag of disorders, but taken as a whole, it exacts an astronomical toll on society. The National Institute of Mental Health says nearly one in five U.S. adults lives with some form of it. According to the World Health Organization, 300 million people worldwide have an anxiety disorder. And there’s a death by suicide every 40 seconds—that includes 20 veterans a day, according to the U.S. Department of Veterans Affairs. Almost 21 million Americans have at least one addiction, per the U.S. Surgeon General, and things are only getting worse. The Lancet Commission—a group of experts in psychiatry, public health, neuroscience, etc.—projects that the cost of mental disorders, currently on the rise in every country, will reach $16 trillion by 2030, including lost productivity. The current standard of care clearly benefits some. Antidepressant medication sales in 2017 surpassed $14 billion. But SSRI drugs—antidepressants that boost the level of serotonin in the brain—can take months to take hold; the first prescription is effective only about 30% of the time. Up to 15% of benzodiazepine users become addicted, and adults on antidepressants are 2.5 times as likely to attempt suicide.

Meanwhile, in various clinical trials, psychedelics are demonstrating both safety and efficacy across the terrain. Scientific papers have been popping up like, well, mushrooms after a good soaking, producing data to blow away conventional methods. Psilocybin, the psychoactive ingredient in magic mushrooms, has been shown to cause a rapid and sustained reduction in anxiety and depression in a group of patients with life-threatening cancer. When paired with counseling, it has improved the ability of some patients suffering from treatment-resistant depression to recognize and process emotion on people’s faces. That correlates to reducing anhedonia, or the inability to feel pleasure. The other psychedelic agent most commonly being studied, MDMA, commonly called ecstasy or molly, has in some scientific studies proved highly effective at treating patients with persistent PTSD. In one Phase II trial of 107 patients who’d had PTSD for an average of over 17 years, 56% no longer showed signs of the affliction after one session of MDMA-assisted therapy. Psychedelics are helping to break addictions, as well. A combination of psilocybin and cognitive therapy enabled 80% of one study’s participants to kick cigarettes for at least six months. Compare that with the 35% for the most effective available smoking-cessation drug, varenicline.

The info is here.

Humility and self-doubt are hallmarks of a good therapist

Helene Nissen-Lie
aeon.co
Originally posted 5 Feb 20

Here is an excerpt:

However, therapist humility on its own is not sufficient for therapy to be effective. In our latest study, we assessed how much therapists treat themselves in a kind and forgiving manner in their personal lives (ie, report more ‘self-affiliation’) and their perceptions of themselves professionally. We anticipated that therapists’ level of personal self-affiliation would enhance the effect that professional self-doubt has on therapeutic change. Our hypothesis was supported: therapists who reported more self-doubt in their work alleviated client distress more if they also reported being kind to themselves outside of work (in contrast, therapists who scored low on self-doubt and high on self-affiliation contributed to the least change).

We interpreted this finding to imply that a benign self-critical stance in a therapist is beneficial, but that self-care and forgiveness without reflective self-criticism is not. The combination of self-affiliation and professional self-doubt seems to pave the way for an open, self-reflective attitude that allows psychotherapists to respect the complexity of their work, and, when needed, to correct the therapeutic course to help clients more effectively.

What does all this mean? At a time when people tend to think that their value is based on how confident they are and that they must ‘sell themselves’ in every situation, the finding that therapist humility is an underrated virtue and a paradoxical ingredient of expertise might be a relief.

The info is here.

A Reality Check On Artificial Intelligence: Are Health Care Claims Overblown?

Liz Szabo
Kaiser Health News
Originally published 30 Dec 19

Here is an excerpt:

“Almost none of the [AI] stuff marketed to patients really works,” said Dr. Ezekiel Emanuel, professor of medical ethics and health policy in the Perelman School of Medicine at the University of Pennsylvania.

The FDA has long focused its attention on devices that pose the greatest threat to patients. And consumer advocates acknowledge that some devices ― such as ones that help people count their daily steps ― need less scrutiny than ones that diagnose or treat disease.

Some software developers don’t bother to apply for FDA clearance or authorization, even when legally required, according to a 2018 study in Annals of Internal Medicine.

Industry analysts say that AI developers have little interest in conducting expensive and time-consuming trials. “It’s not the main concern of these firms to submit themselves to rigorous evaluation that would be published in a peer-reviewed journal,” said Joachim Roski, a principal at Booz Allen Hamilton, a technology consulting firm, and co-author of the National Academy’s report. “That’s not how the U.S. economy works.”

But Oren Etzioni, chief executive officer at the Allen Institute for AI in Seattle, said AI developers have a financial incentive to make sure their medical products are safe.

The info is here.

A systematic review of therapist effects: A critical narrative update and refinement to Baldwin and Imel's (2013) review

Robert G. Johns, Michael Barkham, Stephen Kellett, & David Saxon.
Clinical Psychology Review
Volume 67, February 2019, Pages 78-93

Abstract

Objective

To review the therapist effects literature since Baldwin and Imel's (2013) review.

Method

Systematic literature review of three databases (PsycINFO, PubMed and Web of Science) replicating Baldwin and Imel (2013) search terms. Weighted averages of therapist effects (TEs) were calculated, and a critical narrative review of included studies conducted.

Results

Twenty studies met inclusion criteria (3 RCTs; 17 practice-based) with 19 studies using multilevel modeling. TEs were found in 19 studies. The TE range for all studies was 0.2% to 29% (weighted average = 5%). For RCTs, 1%–29% (weighted average = 8.2%). For practice-based studies, 0.2–21% (weighted average = 5%). The university counseling subsample yielded a lower TE (2.4%) than in other groupings (i.e., primary care, mixed clinical settings, and specialist/focused settings). Therapist sample sizes remained lower than recommended, and few studies appeared to be designed specifically as TE studies, with too few examples of maximising the research potential of large routine patient datasets.

Conclusions

Therapist effects are a robust phenomenon although considerable heterogeneity exists across studies. Patient severity appeared related to TE size. TEs from RCTs were highly variable. Using an overall therapist effects statistic may lack precision, and TEs might be better reported separately for specific clinical settings.

The research is here.

Can Nudges Be Transparent and Yet Effective?

Bruns, Hendrik and Kantorowicz-Reznichenko, Elena and Klement, Katharina and Luistro Jonsson, Marijane and Rahali, Bilel.
Journal of Economic Psychology, Forthcoming. (February 28, 2018).

Abstract

Nudges receive growing attention as an effective concept to alter people's decisions without significantly changing economic incentives or limiting options. However, being often very subtle and covert, nudges are also criticized as unethical.  By not being transparent about the intention to influence individual choice they might be perceived as limiting freedom of autonomous actions and decisions. So far, empirical research on this issue is scarce. In this study, we investigate whether nudges can be made transparent without limiting their effectiveness. For this purpose we conduct a laboratory experiment where we nudge contributions to carbon emission reduction by introducing a default value. We test how different types of transparency (i.e. knowledge of the potential influence of the default, its purpose, or both) influence the effect of the default. Our findings demonstrate that the default increases contributions, and information on the potential influence, its purpose, or both combined do not significantly influence the default effect. Furthermore, we do not find evidence that psychological reactance interacts with the influence of transparency. Findings support the policy-relevant claim that nudges (in the form of defaults) can be transparent and yet effective.

The paper can be downloaded here.

When Evidence Says No, But Doctors Say Yes

David Epstein
ProPublica
Originally published February 22, 2017

Here is an excerpt:

When you visit a doctor, you probably assume the treatment you receive is backed by evidence from medical research. Surely, the drug you’re prescribed or the surgery you’ll undergo wouldn’t be so common if it didn’t work, right?

For all the truly wondrous developments of modern medicine — imaging technologies that enable precision surgery, routine organ transplants, care that transforms premature infants into perfectly healthy kids, and remarkable chemotherapy treatments, to name a few — it is distressingly ordinary for patients to get treatments that research has shown are ineffective or even dangerous. Sometimes doctors simply haven’t kept up with the science. Other times doctors know the state of play perfectly well but continue to deliver these treatments because it’s profitable — or even because they’re popular and patients demand them. Some procedures are implemented based on studies that did not prove whether they really worked in the first place. Others were initially supported by evidence but then were contradicted by better evidence, and yet these procedures have remained the standards of care for years, or decades.

The article is here.

New ruling finally requires homeopathic 'treatments' to obey the same labeling standards as real medicines

Lindsay Dodgson
Business Insider
Originally posted November 17, 2016

The Federal Trade Commission issued a statement this month which said that homeopathic remedies have to be held to the same standard as other products that make similar claims. In other words, American companies must now have reliable scientific evidence for health-related claims that their products can treat specific conditions and illnesses.

The article is here.

The Federal Trade Commission (FTC) ruling is here.

The Science of Choosing Wisely — Overcoming the Therapeutic Illusion

David Casarett
New England Journal of Medicine 2016; 374:1203-1205
March 31, 2016
DOI: 10.1056/NEJMp1516803

Here are two excerpts:

The success of such efforts, however, may be limited by the tendency of human beings to overestimate the effects of their actions. Psychologists call this phenomenon, which is based on our tendency to infer causality where none exists, the “illusion of control.” In medicine, it may be called the “therapeutic illusion” (a label first applied in 1978 to “the unjustified enthusiasm for treatment on the part of both patients and doctors”). When physicians believe that their actions or tools are more effective than they actually are, the results can be unnecessary and costly care. Therefore, I think that efforts to promote more rational decision making will need to address this illusion directly.

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The outcome of virtually all medical decisions is at least partly outside the physician’s control, and random chance can encourage physicians to embrace mistaken beliefs about causality. For instance, joint lavage is overused for relief of osteoarthritis-related knee pain, despite a recommendation against it from the American Academy of Orthopedic Surgery. Knee pain tends to wax and wane, so many patients report improvement in symptoms after lavage, and it’s natural to conclude that the intervention was effective.

The article is here.

Therapist drift redux: Why well-meaning clinicians fail to deliver evidence-based therapy, and how to get back on track

Glenn Waller and Hannah Turner
Behaviour Research and Therapy
Available online 15 December 2015

Abstract

Therapist drift occurs when clinicians fail to deliver the optimum evidence-based treatment despite having the necessary tools, and is an important factor in why those therapies are commonly less effective than they should be in routine clinical practice. The research into this phenomenon has increased substantially over the past five years. This review considers the growing evidence of therapist drift. The reasons that we fail to implement evidence-based psychotherapies are considered, including our personalities, knowledge, emotions, beliefs, behaviors and social milieus. Finally, ideas are offered regarding how therapist drift might be halted, including a cognitive-behavioral approach for therapists that addresses the cognitions, emotions and behaviors that drive and maintain our avoidance of evidence-based treatments.

The research is here.

Neuroscience: Tortured reasoning

Lasana T. Harris
Nature 527, 35–36 (05 November 2015) doi:10.1038/527035a
Published online 04 November 2015

In 2009, following the abuse of prisoners at its Guantanamo Bay detention camp, the US government made a significant decision. It moved the responsibility for 'enhanced interrogation techniques' from the CIA to a new government organization: the High-Value Detainee Interrogation Group (HIG). The move upset many CIA insiders; torture had been in their toolkit since the early days of the cold war. The remarks of one official at a HIG-organized conference on torture in Washington DC can be summed up as: how could a new agency, created to both conduct and study torture, replace the decades of practice and perfection attained by the CIA? By adding a scientific component, responded the newly appointed head of the HIG.

This exchange highlights the theme of neuroscientist Shane O'Mara's Why Torture Doesn't Work. Rightly, O'Mara takes a moral stand against torture (forced retrieval of information from the memories of the unwilling). However, instead of simply providing utilitarian arguments, he argues that there is no evidence from psychology or neuroscience for many of the specious justifications of torture as an information-gathering tool. Providing an abundance of gruesome detail, O'Mara marshals vast, useful information about the effects of such practices on the brain and the body.

(Underline provided by me.)

The entire book review is here.

Making Sex Offenders Pay — and Pay and Pay and Pay:

By Stephen J. Dubner
Freakonomics Podcast
Originally published June 10, 2015

The gist of this episode: Sure, sex crimes are horrific, and the perpetrators deserve to be punished harshly. But society keeps exacting costs — out-of-pocket and otherwise — long after the prison sentence has been served.




The podcast page is here.

College Counseling Centers Turn to Teletherapy to Treat Students for Anxiety

By Jared Misner
Sunoikisis via the Chronicle of Higher Education
Posted September 26, 2014

At the University of Florida, students struggling with anxiety can visit its counseling center and, after an initial, in-person consultation with a counselor, can elect to start a seven-week program called Therapist Assisted Online. The program works like an online course, complete with videos and online activities. Once a week, students meet with their specific counselor, one on one, through a videoconference for 10 to 15 minutes to discuss their anxiety.

That means students visit the counseling center only once and can do the rest from the comfort of their dormitory room. “They like the idea of being at home,” Brian C. Ess, a counselor at Florida’s Counseling and Wellness Center, says.

The entire article is here.

Please visit the Ethics and Psychology podcasts for Episodes 15 and 16, which addresses Ethics and Telepsychology.